Tootfinder

BiTAA: A Bi-Task Adversarial Attack for Object Detection and Depth Estimation via 3D Gaussian Splatting
Yixun Zhang, Feng Zhou, Jianqin Yin
https://arxiv.org/abs/2509.19793 http…

BiTAA: A Bi-Task Adversarial Attack for Object Detection and Depth Estimation via 3D Gaussian Splatting
Camera-based perception is critical to autonomous driving yet remains vulnerable to task-specific adversarial manipulations in object detection and monocular depth estimation. Most existing 2D/3D attacks are developed in task silos, lack mechanisms to induce controllable depth bias, and offer no standardized protocol to quantify cross-task transfer, leaving the interaction between detection and depth underexplored. We present BiTAA, a bi-task adversarial attack built on 3D Gaussian Splatting th…

Zero-shot Multimodal Document Retrieval via Cross-modal Question Generation
Yejin Choi, Jaewoo Park, Janghan Yoon, Saejin Kim, Jaehyun Jeon, Youngjae Yu
https://arxiv.org/abs/2508.17079

Zero-shot Multimodal Document Retrieval via Cross-modal Question Generation
Rapid advances in Multimodal Large Language Models (MLLMs) have expanded information retrieval beyond purely textual inputs, enabling retrieval from complex real world documents that combine text and visuals. However, most documents are private either owned by individuals or confined within corporate silos and current retrievers struggle when faced with unseen domains or languages. To address this gap, we introduce PREMIR, a simple yet effective framework that leverages the broad knowledge of a…

UnifyApps, which lets companies build AI chatbots by connecting SaaS apps and data, raised a $50M Series B led by WestBridge, after a $20M Series A in 2024 (Chris Metinko/Axios)
https://www.axios.com/pro/enterprise-software-deals/2025/10…

Exclusive: UnifyApps raises $50M Series B led by WestBridge Capital
Siloed systems of record and data make it harder for enterprises to adopt AI.

Research in Collaborative Learning Does Not Serve Cross-Silo Federated Learning in Practice
Kevin Kuo, Chhavi Yadav, Virginia Smith
https://arxiv.org/abs/2510.12595 https://

Research in Collaborative Learning Does Not Serve Cross-Silo Federated Learning in Practice
Cross-silo federated learning (FL) is a promising approach to enable cross-organization collaboration in machine learning model development without directly sharing private data. Despite growing organizational interest driven by data protection regulations such as GDPR and HIPAA, the adoption of cross-silo FL remains limited in practice. In this paper, we conduct an interview study to understand the practical challenges associated with cross-silo FL adoption. With interviews spanning a diverse …

Crosslisted article(s) found for cs.DC. https://arxiv.org/list/cs.DC/new
[1/1]:
- A Coopetitive-Compatible Data Generation Framework for Cross-silo Federated Learning
Thanh Linh Nguyen, Quoc-Viet Pham

Crosslisted article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- A Coopetitive-Compatible Data Generation Framework for Cross-silo Federated Learning
Thanh Linh Nguyen, Quoc-Viet Pham

Crosslisted article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- A Coopetitive-Compatible Data Generation Framework for Cross-silo Federated Learning
Thanh Linh Nguyen, Quoc-Viet Pham